Zhiqiang Yao

A method to rationally increase protein stability based on the charge-charge interaction, with application to lipase LipK107.

We report a suite of enzyme redesign protocol based on the surface charge–charge interaction calculation, which is potentially applied to improve the stability of an enzyme without compromising its catalytic activity. Together with the experimental validation, we have released a suite of enzyme redesign algorithm Enzyme Thermal Stability System, written based on our model, for open access to meet the needs in wet labs. Lipk107, a lipase of a versatile industrial use, was chosen to test our software. Our calculation determined that four residues, D113, D149, D213, and D253, located on the surface of LipK107 were critical to the stability of the enzyme. The model was validated with mutagenesis at these four residues followed by stability and activity tests. LipK107 mutants D113A and D149K were more resistant to thermal inactivation with ∼10°C higher half‐inactivation temperature than wild‐type LipK107. Moreover, mutant D149K exhibited significant retention in residual activity under constant heat, showing a 14‐fold increase in the half‐inactivation time at 50°C. Activity tests showed that these mutants retained the equal or higher specific activity, among which noteworthy was the mutant D253A with as much as 20% higher activity. We suggest that our protocol could be used as a general guideline to redesign protein enzymes with increased stabilities and enhanced activities.

The Important Role of Halogen Bond in Substrate Selectivity of Enzymatic Catalysis.

The use of halogen bond is widespread in drug discovery, design, and clinical trials, but is overlooked in drug biosynthesis. Here, the role of halogen bond in the nitrilase-catalyzed synthesis of ortho-, meta-, and para-chlorophenylacetic acid was investigated. Different distributions of halogen bond induced changes of substrate binding conformation and affected substrate selectivity. By engineering the halogen interaction, the substrate selectivity of the enzyme changed, with the implication that halogen bond plays an important role in biosynthesis and should be used as an efficient and reliable tool in enzymatic drug synthesis.

A computational strategy for altering an enzyme in its cofactor preference to NAD(H) and/or NADP(H)

Coenzyme engineering, especially for altered coenzyme specificity, has been a research hotspot for more than a decade. In the present study, a novel computational strategy that enhances the hydrogen‐bond interaction between an enzyme and a coenzyme was developed and utilized to alter the coenzyme preference. This novel computational strategy only required the structure of the target enzyme. No other homologous enzymes were needed to achieve alteration in the coenzyme preference of a certain enzyme. Using our novel strategy, Gox2181 was reconstructed from exhibiting complete NADPH preference to exhibiting dual cofactor specificity for NADH and NADPH. Structure‐guided Gox2181 mutants were designed in silico and molecular dynamics simulations were performed to evaluate the strength of hydrogen‐bond interactions between the enzyme and the coenzyme NADPH. Three Gox2181 mutants displaying high structure stability and structural compatibility to NADH/NADPH were chosen for experimental confirmation. Among the three Gox2181 mutants, Gox2181‐Q20R&D43S showed the highest enzymatic activity by utilizing NADPH as its coenzyme, which was even better than the wild‐type enzyme. In addition, isothermal titration calorimetry analysis further verified that Gox2181‐Q20R&D43S was able to interact with NADPH but the wild‐type enzyme could not. This novel computational strategy represents an insightful approach for altering the cofactor preference of target enzymes.

Towards the computational design and engineering of enzyme enantioselectivity: A case study by a carbonyl reductase from Gluconobacter oxydans.

In our previous work, a NAD(H)-dependent carbonyl reductase (GoCR) was identified from Gluconobacter oxydans, which showed moderate to high enantiospecificity for the reduction of different kinds of prochiral ketones. In the present study, the crystal structure of GoCR was determined at 1.65Å resolution, and a computational strategy concerning substrate-enzyme docking and all-atom molecular dynamics (MD) simulation was established to help understand the molecular basis of enantiopreference and enantiorecognition for GoCR, and to further guide the design and engineering of GoCR enantioselectivity. For the reduction of ethyl 2-oxo-4-phenylbutyrate (OPBE), three binding pocket residues, Cys93, Tyr149, and Trp193 were predicted to play a critical role in determining the enantioselectivity. Through site-directed mutagenesis, single-point mutant W193A was constructed and proved to reduce OPBE to ethyl (R)-2-hydroxy-4-phenylbutyrate (R-HPBE) with a significantly improved ee of >99% compared to 43.2% for the wild type (WT). Furthermore, double mutant C93V/Y149A was proved to even invert the enantioselectivity of GoCR to afford S-HPBE at 79.8% ee.

Structural and mutational studies on an aldo-keto reductase AKR5C3 from Gluconobacter oxydans

An aldo‐keto reductase AKR5C3 from Gluconobacter oxydans (designated as Gox0644) is a useful enzyme with various substrates, including aldehydes, diacetyl, keto esters, and α‐ketocarbonyl compounds. The crystal structures of AKR5C3 in apoform in complex with NADPH and the D53A mutant (AKR5C3‐D53A) in complex with NADPH are presented herein. Structure comparison and site‐directed mutagenesis combined with biochemical kinetics analysis reveal that the conserved Asp53 in the AKR5C3 catalytic tetrad has a crucial role in securing active pocket conformation. The gain‐of‐function Asp53 to Ala mutation triggers conformational changes on the Trp30 and Trp191 side chains, improving NADPH affinity to AKR5C3, which helps increase catalytic efficiency. The highly conserved Trp30 and Trp191 residues interact with the nicotinamide moiety of NADPH and help form the NADPH‐binding pocket. The AKR5C3‐W30A and AKR5C3‐W191Y mutants show decreased activities, confirming that both residues facilitate catalysis. Residue Trp191 is in the loop structure, and the AKR5C3‐W191Y mutant does not react with benzaldehyde, which might also determine substrate recognition. Arg192, which is involved in the substrate binding, is another important residue. The introduction of R192G increases substrate‐binding affinity by improving hydrophobicity in the substrate‐binding pocket. These results not only supplement the AKRs superfamily with crystal structures but also provide useful information for understanding the catalytic properties of AKR5C3 and guiding further engineering of this enzyme.

Crius: A novel fragment-based algorithm of de novo substrate prediction for enzymes: Crius: Substrate Prediction Algorithm for Enzymes

The study of enzyme substrate specificity is vital for developing potential applications of enzymes. However, the routine experimental procedures require lot of resources in the discovery of novel substrates. This article reports an in silico structure‐based algorithm called Crius, which predicts substrates for enzyme. The results of this fragment‐based algorithm show good agreements between the simulated and experimental substrate specificities, using a lipase from Candida antarctica (CALB), a nitrilase from Cyanobacterium syechocystis sp. PCC6803 (Nit6803), and an aldo‐keto reductase from Gluconobacter oxydans (Gox0644). This opens new prospects of developing computer algorithms that can effectively predict substrates for an enzyme.

Switching a nitrilase from Syechocystis sp. PCC6803 to a nitrile hydratase by rationally regulating reaction pathways

The development of robust biocatalysts producing a large range of organic amides by hydration of nitriles is an important pursuit and challenge. A nitrilase with a broad range of nitrile substrates was switched to a nitrile hydratase by rationally regulating the reaction pathways. Five mutants improved the amide formation in the product, and four of them formed >50% amide. F193N, with the highest amide formation among the four mutants, improved its amide product up to 73%, which was 35-fold that of the wild type, while maintaining 50% activity relative to the wild type. This study would afford a new synthetic route to amides from nitriles and could be a valuable addition to the synthetic repertoire. Further protein engineering may expand the reaction range of an enzyme to afford more additional pathways to synthetic biology.